The advection of integral lines is an important computational kernel in vector field visualization. We investigate how this kernel can profit from vector (SIMD) extensions in modern CPUs. As a baseline, we formulate a streamline tracing algorithm that facilitates auto-vectorization by an optimizing compiler. We analyze this algorithm and propose two different optimizations. Our results show that particle tracing does not per se benefit from SIMD computation. Based on a careful analysis of the auto-vectorized code, we propose an optimized data access routine and a re-packing scheme which increases average SIMD efficiency. We evaluate our approach on three different, turbulent flow fields. Our optimized approaches increase integration performance up to 5:6 over our baseline measurement. We conclude with a discussion of current limitations and aspects for future work.

@INPROCEEDINGS{Hentschel2015, author = {Bernd Hentschel and Jens Henrik G{\"o}bbert and Michael Klemm andPaul Springer and Andrea Schnorr and Torsten W. Kuhlen}, title = {{P}acket-{O}riented {S}treamline {T}racing on {M}odern {SIMD}{A}rchitectures}, booktitle = {Proceedings of the Eurographics Symposium on Parallel Graphicsand Visualization}, year = {2015}, pages = {43--52}, abstract = {The advection of integral lines is an important computationalkernel in vector field visualization. We investigatehow this kernel can profit from vector (SIMD) extensions in modern CPUs. As abaseline, we formulate a streamlinetracing algorithm that facilitates auto-vectorization by an optimizing compiler.We analyze this algorithm andpropose two different optimizations. Our results show that particle tracing doesnot per se benefit from SIMD computation.Based on a careful analysis of the auto-vectorized code, we propose an optimizeddata access routineand a re-packing scheme which increases average SIMD efficiency. We evaluate ourapproach on three different,turbulent flow fields. Our optimized approaches increase integration performanceup to 5.6x over our baselinemeasurement. We conclude with a discussion of current limitations and aspectsfor future work.}}